相关论文: Detecting anomalous quartic gauge couplings using …

Isolation forest (iForest) has been emerging as arguably the most popular anomaly detector in recent years due to its general effectiveness across different benchmarks and strong scalability. Nevertheless, its linear axis-parallel isolation…

The search for quartic anomalous gauge couplings at LEP requires appropriate predictions for the radiative processes e+ e- \to \nu\bar\nu \gamma\gamma, e+ e- \to q\bar{q}\gamma\gamma and e+ e- \to 4 fermions+\gamma. Matrix elements are…

We present the first evidence that adaptive learning techniques can boost the discovery of unusual objects within astronomical light curve data sets. Our method follows an active learning strategy where the learning algorithm chooses…

In this paper, the mathematical analysis of the Isolation Random Forest Method (IRF Method) for anomaly detection is presented. We show that the IRF space can be endowed with a probability induced by the Isolation Tree algorithm (iTree). In…

The detection of anomalous behaviours is an emerging need in many applications, particularly in contexts where security and reliability are critical aspects. While the definition of anomaly strictly depends on the domain framework, it is…

We present a new algorithm for anomaly detection called Anomaly Awareness. The algorithm learns about normal events while being made aware of the anomalies through a modification of the cost function. We show how this method works in…

The Interest Public Group ARRONAX's C70XP cyclotron, used for radioisotope production for medical and research applications, relies on complex and costly systems that are prone to failures, leading to operational disruptions. In this…

The muon collider provides a unique opportunity to study the vector boson scattering processes and dimension-8 operators contributing to anomalous quartic gauge couplings~(aQGCs). Because of the cleaner final state, it is easier to decode…

Anomaly detection is critical in various fields, including intrusion detection, health monitoring, fault diagnosis, and sensor network event detection. The isolation forest (or iForest) approach is a well-known technique for detecting…

The search for quartic anomalous gauge couplings (QAGC) at LEP requires appropriate predictions for the radiative processes e+ e- \to \nu\bar\nu \gamma\gamma, e+ e- \to q\bar{q}\gamma\gamma and e+ e- \to 4 fermions+\gamma. The current…

Unsupervised anomaly detection tackles the problem of finding anomalies inside datasets without the labels availability; since data tagging is typically hard or expensive to obtain, such approaches have seen huge applicability in recent…

As cyber threats continue to evolve in sophistication and scale, the ability to detect anomalous network behavior has become critical for maintaining robust cybersecurity defenses. Modern cybersecurity systems face the overwhelming…

The vector boson scattering (VBS) processes in Large Hadron Collider (LHC) experiments offer a unique opportunity to probe the anomalous quartic gauge couplings (aQGCs). We study the dimension-8 operators contributing to the anomalous…

The investigation of quartic gauge couplings provides a crucial test of the Standard Model and serves as a potential window into new physics at higher energy scales. Within the framework of Effective Field Theory, deviations from the SM can…

A Normalizing Flow computes a bijective mapping from an arbitrary distribution to a predefined (e.g. normal) distribution. Such a flow can be used to address different tasks, e.g. anomaly detection, once such a mapping has been learned. In…

Non-Abelian structure of the Standard Model predicts the self-interactions of gauge bosons triple gauge couplings (TGC) and quartic gauge couplings (QGC). On the other hand, it is also important to determine the deviations from Standard…

A new modification of Isolation Forest called Attention-Based Isolation Forest (ABIForest) for solving the anomaly detection problem is proposed. It incorporates the attention mechanism in the form of the Nadaraya-Watson regression into the…

Recently, federated learning frameworks such as Python TestBed for Federated Learning Algorithms and MicroPython TestBed for Federated Learning Algorithms have emerged to tackle user privacy concerns and efficiency in embedded systems. Even…

The Isolation Forest (iForest), proposed by Liu, Ting, and Zhou at TKDE 2012, has become a prominent tool for unsupervised anomaly detection. However, recent research by Hariri, Kind, and Brunner, published in TKDE 2021, has revealed issues…

Anomaly Detection is an unsupervised learning task aimed at detecting anomalous behaviours with respect to historical data. In particular, multivariate Anomaly Detection has an important role in many applications thanks to the capability of…